Decision Making Methods for Water Resources Management Under Deep Uncertainty Submitted by Thomas Peter Roach to the University of Exeter as a thesis for the degree of Doctor of Engineering in Water Engineering In October 2016 This thesis is available for Library use on the understanding that it is copyright material and that no quotation from the thesis may be published without proper acknowledgement. I certify that all material in this thesis which is not my own work has been identified and that no material has previously been submitted and approved for the award of a degree by this or any other University. Signature: ………………………………………………………….. 2 Abstract Substantial anthropogenic change of the Earth’s climate is modifying patterns of rainfall, river flow, glacial melt and groundwater recharge rates across the planet, undermining many of the stationarity assumptions upon which water resources infrastructure has been historically managed. This hydrological uncertainty is creating a potentially vast range of possible futures that could threaten the dependability of vital regional water supplies. This, combined with increased urbanisation and rapidly growing regional populations, is putting pressures on finite water resources. One of the greatest international challenges facing decision makers in the water industry is the increasing influences of these “deep” climate change and population growth uncertainties affecting the long-term balance of supply and demand and necessitating the need for adaptive action. Water companies and utilities worldwide are now under pressure to modernise their management frameworks and approaches to decision making in order to identify more sustainable and cost-effective water management adaptations that are reliable in the face of uncertainty. The aim of this thesis is to compare and contrast a range of existing Decision Making Methods (DMMs) for possible application to Water Resources Management (WRM) problems, critically analyse on real-life case studies their suitability for handling uncertainties relating to climate change and population growth and then use the knowledge generated this way to develop a new, resilience-based WRM planning methodology. This involves a critical evaluation of the advantages and disadvantages of a range of methods and metrics developed to improve on current engineering practice, to ultimately compile a list of suitable recommendations for a future framework for WRM adaptation planning under deep uncertainty. This thesis contributes to the growing vital research and literature in this area in several distinct ways. Firstly, it qualitatively reviews a range of DMMs for potential application to WRM adaptation problems using a set of developed criteria. Secondly, it quantitatively assesses two promising and contrasting DMMs on two suitable real-world case studies to compare highlighted aspects derived from the qualitative review and evaluate the adaptation outputs on a 3 practical engineering level. Thirdly, it develops and reviews a range of new potential performance metrics that could be used to quantitatively define system resilience to help answer the water industries question of how best to build in more resilience in future water resource adaptation planning. This leads to the creation and testing of a novel resilience driven methodology for optimal water resource planning, combining optimal aspects derived from the quantitative case study work with the optimal metric derived from the resilience metric investigation. Ultimately, based on the results obtained, a list of suitable recommendations is compiled on how to improve the existing methodologies for future WRM planning under deep uncertainty. These recommendations include the incorporation of more complex simulation models into the planning process, utilisation of multi-objective optimisation algorithms, improved uncertainty characterisation and assessments, an explicit robustness examination and the incorporation of additional performance metrics to increase the clarity of the strategy assessment process. 4 Acknowledgments I would first like to express my earnest thanks to my academic supervisor Professor Zoran Kapelan and my industrial supervisors Dr Ralph Ledbetter and Dr Michelle Ledbetter, whose continued support and guidance throughout this EngD project has been invaluable to the completion of this thesis. I am extremely grateful for their tireless assistance and for sharing the wealth of their knowledge and expertise, allowing this research to reach its full potential. I would also like to thank Dr Mark Siddorn and Dr David Wyncoll for their advice and assistance with all things computational and for their attempts to turn me into a competent computer programmer. Thanks also go to Chris Counsell, Dr Steven Wade and Ben Gouldby of HR Wallingford for lending their knowledge and experience during the early stages of this research project. I also gratefully acknowledge the financial support from the UK Engineering and Physical Sciences Research Council (EPSRC) through funding of the STREAM Industrial Doctorate Centre, and from the project sponsor HR Wallingford. I would also like to acknowledge my fellow researchers within my STREAM cohort year; who have provided an indispensable comradeship during this often solitary journey. Thanks also go to the Doherty family and Oxford University Judo Club, who gave me a welcoming and supportive place to go when a much needed mental break was required. Finally, I would like to thank my family and friends, especially my parents Trevor and Teresa and brother Gareth. Without your support and encouragement this thesis could not have been completed. 5 Table of Contents Abstract .............................................................................................................. 3 Acknowledgments .............................................................................................. 5 List of Figures ................................................................................................... 10 List of Tables .................................................................................................... 13 List of Abbreviations ......................................................................................... 14 Chapter 1. Introduction .................................................................................. 16 1.1 Background and motivation of research .............................................. 16 1.2 Overall aim and objectives .................................................................. 19 1.3 Thesis Structure .................................................................................. 21 Chapter 2. Literature Review ......................................................................... 25 2.1 Introduction ......................................................................................... 25 2.2 Overview of water resource management (WRM) problem ................. 25 2.3 The history, evolution and current practice of WRM (in the UK) .......... 26 2.3.1 WRM in the UK (1940-1980)......................................................... 26 2.3.2 WRM in the UK (1980-2015)......................................................... 27 2.3.3 WRM in the UK (2016 and beyond) .............................................. 28 2.3.4 Current WRM planning approaches (UK and international) .......... 29 2.4 Key future uncertainties for WRM........................................................ 33 2.4.1 Future supply uncertainties ........................................................... 33 2.4.2 Future demand uncertainties ........................................................ 35 2.5 Definitions of key terminology in WRM adaptation planning ................ 36 2.5.1 WRM Problem definition ............................................................... 36 2.5.2 Decision Making Methods (DMMs) ............................................... 37 2.5.3 Deep uncertainty ........................................................................... 37 2.5.4 Adaptation strategy ....................................................................... 38 2.5.5 Future scenarios (of supply and demand) .................................... 38 2.5.6 Robustness ................................................................................... 41 2.5.7 Performance metrics – resilience, reliability and vulnerability ....... 42 2.5.8 Flexibility ....................................................................................... 44 2.5.9 Risk-based planning ..................................................................... 45 2.6 Approaches for WRM adaptation planning under deep uncertainty .... 45 6 2.7 Summary ............................................................................................. 53 Chapter 3. Qualitative Comparison of Existing DMMs for WRM Under Uncertainty ...................................................................................................... 54 3.1 Introduction ......................................................................................... 54 3.2 Decision making methods under review .............................................. 54 3.2.1 (i) Info-Gap decision theory (IG) ................................................... 55 3.2.2 (ii) Robust Optimisation (RO) ........................................................ 57 3.2.3 (iii) Robust Decision Making (RDM) .............................................. 58 3.2.4 (iv) Decision-Scaling (DS) ............................................................